Inter-Cell Interference Rejection Based on Ultrawideband Walsh-Domain Wireless Autoencoding

2026-01-16

AI Summary

This work addresses the challenge of partial in-band inter-cell interference (ICI) from coexisting 5G base stations in ultra-wideband communication systems. To mitigate this interference, the authors propose a Walsh-domain end-to-end wireless autoencoder architecture that, for the first time, leverages the orthogonality and self-duality properties of Walsh functions within a wireless autoencoder framework. By jointly optimizing the transmitter and receiver encoders and decoders, the approach distributes bit information across multiple Walsh branches to suppress ICI. Through analysis of the mapping characteristics of 5G CPOFDM signals in the Walsh domain, the optimal transmission frequency and sampling rate configuration is identified. Experimental results demonstrate that the proposed method achieves up to 12 dB of ICI suppression gain while maintaining the same signal-to-noise ratio and a low block error rate (BLER).

Technology Category

• Cognitive Modeling & Cognitive Systems: Neural Spike Coding
• Machine Learning: Deep Generative Models & Autoencoders
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

This paper proposes a novel technique for rejecting partial-in-band inter-cell interference (ICI) in ultrawideband communication systems. We present the design of an end-to-end wireless autoencoder architecture that jointly optimizes the transmitter and receiver encoding/decoding in the Walsh domain to mitigate interference from coexisting narrower-band 5G base stations. By exploiting the orthogonality and self-inverse properties of Walsh functions, the system distributes and learns to encode bit-words across parallel Walsh branches. Through analytical modeling and simulation, we characterize how 5G CPOFDM interference maps into the Walsh domain and identify optimal ratios of transmission frequencies and sampling rate where the end-to-end autoencoder achieves the highest rejection. Experimental results show that the proposed autoencoder achieves up to 12 dB of ICI rejection while maintaining a low block error rate (BLER) for the same baseline channel noise, i.e., baseline Signal-to-Noise-Ratio (SNR) without the interference.

Problem

• Inter-Cell Interference
• Ultrawideband
• Walsh Domain
• 5G Interference
• In-Band Interference

Innovation

• Walsh-domain autoencoding
• inter-cell interference rejection
• ultrawideband communication
• end-to-end wireless learning
• orthogonal signal representation